Upload 8 files

README.md

@@ -1,3 +1,204 @@
 ---
-license: cc-by-nc-4.0
+library_name: peft
+base_model: 152334H/miqu-1-70b-sf
 ---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+### Framework versions
+
+- PEFT 0.8.2

adapter_config.json

@@ -0,0 +1,33 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "152334H/miqu-1-70b-sf",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "gate_proj",
+    "lm_head",
+    "k_proj",
+    "down_proj",
+    "up_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:97c230a45fc519978a9346af3a733080889b9845a41a4f42e642eea9fe912eb9
+size 2710625064

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aed1570f3a4ccf9341b0456b3c72ed7c212b45e1682a3bcfab2f451ae1485932
+size 833909276

rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb487b0d77992419a65e0dcf3a28307a1228f2bed886f9d37be5624351535ca6
+size 14244

scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23bc35f5d3e0b31fa9ca7317d9a8df102eb3e18f3c11a7f544431af9ffe93353
+size 1064

trainer_state.json

@@ -0,0 +1,229 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 2.056555269922879,
+  "eval_steps": 400,
+  "global_step": 800,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.06,
+      "learning_rate": 0.00019903980796159233,
+      "loss": 1.2452,
+      "step": 25
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 0.00019803960792158433,
+      "loss": 1.2141,
+      "step": 50
+    },
+    {
+      "epoch": 0.19,
+      "learning_rate": 0.00019703940788157634,
+      "loss": 1.1351,
+      "step": 75
+    },
+    {
+      "epoch": 0.26,
+      "learning_rate": 0.00019603920784156832,
+      "loss": 1.1895,
+      "step": 100
+    },
+    {
+      "epoch": 0.32,
+      "learning_rate": 0.00019503900780156033,
+      "loss": 1.1864,
+      "step": 125
+    },
+    {
+      "epoch": 0.39,
+      "learning_rate": 0.0001940388077615523,
+      "loss": 1.1171,
+      "step": 150
+    },
+    {
+      "epoch": 0.45,
+      "learning_rate": 0.00019303860772154432,
+      "loss": 1.2292,
+      "step": 175
+    },
+    {
+      "epoch": 0.51,
+      "learning_rate": 0.00019203840768153632,
+      "loss": 1.1102,
+      "step": 200
+    },
+    {
+      "epoch": 0.58,
+      "learning_rate": 0.0001910382076415283,
+      "loss": 1.2064,
+      "step": 225
+    },
+    {
+      "epoch": 0.64,
+      "learning_rate": 0.0001900380076015203,
+      "loss": 1.2256,
+      "step": 250
+    },
+    {
+      "epoch": 0.71,
+      "learning_rate": 0.0001890378075615123,
+      "loss": 1.1175,
+      "step": 275
+    },
+    {
+      "epoch": 0.77,
+      "learning_rate": 0.0001880376075215043,
+      "loss": 1.098,
+      "step": 300
+    },
+    {
+      "epoch": 0.84,
+      "learning_rate": 0.00018703740748149633,
+      "loss": 1.299,
+      "step": 325
+    },
+    {
+      "epoch": 0.9,
+      "learning_rate": 0.0001860372074414883,
+      "loss": 1.1586,
+      "step": 350
+    },
+    {
+      "epoch": 0.96,
+      "learning_rate": 0.00018503700740148032,
+      "loss": 1.202,
+      "step": 375
+    },
+    {
+      "epoch": 1.03,
+      "learning_rate": 0.0001840368073614723,
+      "loss": 1.0137,
+      "step": 400
+    },
+    {
+      "epoch": 1.03,
+      "eval_loss": 0.8309869766235352,
+      "eval_runtime": 1939.5005,
+      "eval_samples_per_second": 0.401,
+      "eval_steps_per_second": 0.051,
+      "step": 400
+    },
+    {
+      "epoch": 1.09,
+      "learning_rate": 0.0001830366073214643,
+      "loss": 0.7305,
+      "step": 425
+    },
+    {
+      "epoch": 1.16,
+      "learning_rate": 0.0001820364072814563,
+      "loss": 0.8463,
+      "step": 450
+    },
+    {
+      "epoch": 1.22,
+      "learning_rate": 0.0001810362072414483,
+      "loss": 0.7727,
+      "step": 475
+    },
+    {
+      "epoch": 1.29,
+      "learning_rate": 0.0001800360072014403,
+      "loss": 0.8441,
+      "step": 500
+    },
+    {
+      "epoch": 1.35,
+      "learning_rate": 0.00017903580716143228,
+      "loss": 0.757,
+      "step": 525
+    },
+    {
+      "epoch": 1.41,
+      "learning_rate": 0.00017803560712142429,
+      "loss": 0.7867,
+      "step": 550
+    },
+    {
+      "epoch": 1.48,
+      "learning_rate": 0.0001770354070814163,
+      "loss": 0.8074,
+      "step": 575
+    },
+    {
+      "epoch": 1.54,
+      "learning_rate": 0.0001760352070414083,
+      "loss": 0.7697,
+      "step": 600
+    },
+    {
+      "epoch": 1.61,
+      "learning_rate": 0.0001750350070014003,
+      "loss": 0.8323,
+      "step": 625
+    },
+    {
+      "epoch": 1.67,
+      "learning_rate": 0.0001740348069613923,
+      "loss": 0.7122,
+      "step": 650
+    },
+    {
+      "epoch": 1.74,
+      "learning_rate": 0.0001730346069213843,
+      "loss": 0.7781,
+      "step": 675
+    },
+    {
+      "epoch": 1.8,
+      "learning_rate": 0.00017203440688137627,
+      "loss": 0.8105,
+      "step": 700
+    },
+    {
+      "epoch": 1.86,
+      "learning_rate": 0.00017103420684136828,
+      "loss": 0.812,
+      "step": 725
+    },
+    {
+      "epoch": 1.93,
+      "learning_rate": 0.0001700340068013603,
+      "loss": 0.7918,
+      "step": 750
+    },
+    {
+      "epoch": 1.99,
+      "learning_rate": 0.00016903380676135227,
+      "loss": 0.7319,
+      "step": 775
+    },
+    {
+      "epoch": 2.06,
+      "learning_rate": 0.00016803360672134428,
+      "loss": 0.309,
+      "step": 800
+    },
+    {
+      "epoch": 2.06,
+      "eval_loss": 0.2903744876384735,
+      "eval_runtime": 1946.3315,
+      "eval_samples_per_second": 0.399,
+      "eval_steps_per_second": 0.05,
+      "step": 800
+    }
+  ],
+  "logging_steps": 25,
+  "max_steps": 5000,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 13,
+  "save_steps": 400,
+  "total_flos": 1.3574517302954557e+18,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:514ff4a09a2df35d48e2f4a93ca8d0892d973cbf184b1afa38f7f651c980337f
+size 4728